This paper reports our experiments on the concept detection task of TRECVID 2007. In these experiments, we have addressed two approaches which are selecting and fusing features and kernel-based learning method. As for the former one, we investigate the following issues: (i) which features are more appropriate for the concept detection task?, (ii) whether the fusion of features can help to impro...

These working notes paper present the contribution of the UPC team to the Hyperlinking sub-task of the Search and Hyperlinking Task in MediaEval 2013. Our contribution explores the potential of a solution based only on visual cues. In particular, every automatically generated shot is represented by a keyframe. The linking between video segments is based on the visual similarity of the keyframes...

In this paper, we present human pose estimation and gesture recognition algorithms that use only depth information. The proposed methods are designed to be operated with only a CPU (central processing unit), so that the algorithm can be operated on a low-cost platform, such as an embedded board. The human pose estimation method is based on an SVM (support vector machine) and superpixels without...

Despite much interest in Simultaneous Localization and Mapping (SLAM), there is a lack of efficient methods for representing and processing their large scale point clouds. In this paper, we propose to simplify the point clouds generated by the semi-dense SLAM using three-dimensional (3D) line segments. Specifically, we present a novel incremental approach for 3D line segments extraction. This a...

This paper introduces a non-parametric sequential frame decimation algorithm for image sequences in low-memory streaming environments. Frame decimation reduces the number of input frames to increase pose and structure robustness in Structure and Motion (SaM) applications. The main contribution of this paper is the introduction of a sequential low-memory work-flow for frame decimation in embedde...

This paper describes the participation of MIRACLE research consortium at the VideoCLEF track at CLEF 2008. We took part in both the main mandatory Classification task that consists in classifying videos of television episodes using speech transcripts and metadata, and the Keyframe Extraction task, whose objective is to select keyframes that represent individual episodes from a set of supplied k...

Home video collections constitute an important source of content to be experienced within the digital entertainment context. To make such content easy to access and reuse, various video analysis technologies have been researched and developed to extract video assets for management tasks, including video shot/scene detection, keyframe extraction, and video skimming/summarization. However, one le...

Descriptor-based image registration consists of many processing stages. Errors introduced by the keyframe localization stage (whose magnitude correlates with the disparity between the images) are usually neglected, or corrected by computationally intensive optical flow methods. Results presented by this paper target a faster solution to this problem. It is based on the investigation, how the Se...

Despite much interest in Simultaneous Localization and Mapping (SLAM), there is a lack of efficient methods for representing and processing their large scale point clouds. In this paper, we propose to simplify the point clouds generated by the semi-dense SLAM using three-dimensional (3D) line segments. Specifically, we present a novel incremental approach for 3D line segments extraction. This a...